Used Textbook

eTextbook

New Textbook

Related Products

Connect Plus Access Card for Basic Statistics for Business and Economics

Premium Content Access Card for Basic Statistics in Business and Economics

Connect Access Card for Basic Statistics Business end Economics

Basic Business Statistics for Business and Economics with Formula Card + Connect Plus

Gen Cmb Bas Stats B&E; Aleks Prep

Gen Cmb Bas Stat B&E; Aleks 1Sem

Gen Cmbo Bas Stat B&E; Alks Prep;Cnct+

Gen Cmbo Bas Stat B&E; Alks Prep;Alks 1S

Basic Statistics for Business and Economics with Student CD-ROM

Summary

The Fifth Edition of Basic Statistics for Business and Economics is a shorter version of Lind/Marchal/Wathen's Statistical Techniques in Business and Economics, 12e. The authors of this text continue to provide a student-oriented approach to business statistics. In this book you will find step-by-step solved examples, realistic exercises, and up-to-date technology and illustrations. Book jacket.

Table of Contents

What Is Statistics?

p. 1

Introduction

p. 2

Why Study Statistics?

p. 2

What Is Meant by Statistics?

p. 4

Types of Statistics

p. 6

Descriptive Statistics

p. 6

Inferential Statistics

p. 7

Types of Variables

p. 9

Levels of Measurement

p. 9

Nominal-Level Data

p. 10

Ordinal-Level Data

p. 11

Interval-Level Data

p. 12

Ratio-Level Data

p. 12

Exercises

p. 14

Statistics, Graphics, and Ethics

p. 15

Misleading Statistics

p. 15

Association Does Not Necessarily Imply Causation

p. 15

Graphs Can Be Misleading

p. 16

Become a Better Consumer and a Better Producer of Information

p. 17

Ethics

p. 17

Software Applications

p. 18

Chapter Outline

p. 19

Chapter Exercises

p. 19

exercises.com

p. 20

Dataset Exercises

p. 21

Answers to Self-Review

p. 22

Describing Data: Frequency Distributions and Graphic Presentation

p. 23

Introduction

p. 24

Constructing a Frequency Distribution

p. 25

Class Intervals and Class Midpoints

p. 29

A Software Example

p. 29

Relative Frequency Distribution

p. 30

Exercises

p. 31

Graphic Presentation of a Frequency Distribution

p. 32

Histogram

p. 32

Frequency Polygon

p. 34

Exercises

p. 37

Cumulative Frequency Distributions

p. 38

Exercises

p. 41

Other Graphic Presentations of Data

p. 42

Line Graphs

p. 42

Bar Charts

p. 43

Pie Charts

p. 44

Exercises

p. 46

Chapter Outline

p. 47

Chapter Exercises

p. 48

exercises.com

p. 53

Dataset Exercises

p. 53

Software Commands

p. 54

Answers to Self-Review

p. 56

Describing Data: Numerical Measures

p. 57

Introduction

p. 58

The Population Mean

p. 59

The Sample Mean

p. 60

Properties of the Arithmetic Mean

p. 61

Exercises

p. 62

The Weighted Mean

p. 63

Exercises

p. 64

The Median

p. 64

The Mode

p. 65

Exercises

p. 67

Software Solution

p. 68

The Relative Positions of the Mean, Median, and Mode

p. 68

Exercises

p. 70

The Geometric Mean

p. 71

Exercises

p. 72

Why Study Dispersion?

p. 73

Measures of Dispersion

p. 74

Range

p. 74

Mean Deviation

p. 75

Exercises

p. 76

Variance and Standard Deviation

p. 77

Exercises

p. 79

Software Solution

p. 80

Exercises

p. 81

Interpretation and Uses of the Standard Deviation

p. 82

Chebyshev's Theorem

p. 82

The Empirical Rule

p. 83

Exercises

p. 84

Chapter Outline

p. 84

Pronunciation Key

p. 86

Chapter Exercises

p. 86

exercises.com

p. 89

Dataset Exercises

p. 90

Software Commands

p. 90

Answers to Self-Review

p. 92

Describing Data: Displaying and Exploring Data

p. 93

Introduction

p. 94

Dot Plots

p. 94

Exercises

p. 96

Quartiles, Deciles, and Percentiles

p. 97

Exercises

p. 100

Box Plots

p. 100

Exercises

p. 102

Skewness

p. 103

Exercises

p. 107

Describing the Relationship between Two Variables

p. 107

Exercises

p. 110

Chapter Outline

p. 112

Pronunciation Key

p. 112

Chapter Exercises

p. 112

exercises.com

p. 116

Dataset Exercises

p. 116

Software Commands

p. 117

Answers to Self-Review

p. 119

A Survey of Probability Concepts

p. 120

Introduction

p. 121

What Is a Probability?

p. 122

Approaches to Assigning Probabilities

p. 124

Classical Probability

p. 124

Empirical Probability

p. 125

Subjective Probability

p. 126

Exercises

p. 127

Some Rules for Computing Probabilities

p. 128

Rules of Addition

p. 128

Exercises

p. 133

Rules of Multiplication

p. 134

Contingency Tables

p. 137

Tree Diagrams

p. 139

Exercises

p. 141

Principles of Counting

p. 142

The Multiplication Formula

p. 142

The Permutation Formula

p. 143

The Combination Formula

p. 145

Exercises

p. 146

Chapter Outline

p. 147

Pronunciation Key

p. 148

Chapter Exercises

p. 148

exercises.com

p. 152

Dataset Exercises

p. 152

Software Commands

p. 153

Answers to Self-Review

p. 154

Discrete Probability Distributions

p. 156

Introduction

p. 157

What Is a Probability Distribution?

p. 157

Random Variables

p. 159

Discrete Random Variable

p. 159

Continuous Random Variable

p. 160

The Mean, Variance, and Standard Deviation of a Probability Distribution

p. 160

Mean

p. 160

Variance and Standard Distribution

p. 161

Exercises

p. 163

Binomial Probability Distribution

p. 164

How Is a Binomial Probability Distribution Computed

p. 165

Binomial Probability Tables

p. 167

Exercises

p. 170

Cumulative Binomial Probability Distributions

p. 172

Exercises

p. 173

Poisson Probability Distribution

p. 174

Exercises

p. 177

Chapter Outline

p. 177

Chapter Exercises

p. 178

Dataset Exercises

p. 182

Software Commands

p. 182

Answers to Self-Review

p. 184

Continuous Probability Distributions

p. 185

Introduction

p. 186

The Family of Uniform Distributions

p. 186

Exercises

p. 189

The Family of Normal Probability Distributions

p. 190

The Standard Normal Distribution

p. 193

The Empirical Rule

p. 195

Exercises

p. 196

Finding Areas under the Normal Curve

p. 197

Exercises

p. 199

Exercises

p. 202

Exercises

p. 204

Chapter Outline

p. 204

Chapter Exercises

p. 205

Dataset Exercises

p. 208

Software Commands

p. 209

Answers to Self-Review

p. 210

Sampling Methods and the Central Limit Theorem

p. 211

Introduction

p. 212

Sampling Methods

p. 212

Reasons to Sample

p. 212

Simple Random Sampling

p. 213

Systematic Random Sampling

p. 216

Stratified Random Sampling

p. 216

Cluster Sampling

p. 217

Exercises

p. 218

Sampling "Error"

p. 220

Sampling Distribution of the Sample Mean

p. 222

Exercises

p. 225

The Central Limit Theorem

p. 226

Exercises

p. 232

Using the Sampling Distribution of the Sample Mean

p. 233

Exercises

p. 237

Chapter Outline

p. 237

Pronunciation Key

p. 238

Chapter Exercises

p. 238

exercises.com

p. 242

Dataset Exercises

p. 243

Software Commands

p. 243

Answers to Self-Review

p. 244

Estimation and Confidence Intervals

p. 245

Introduction

p. 246

Point Estimates and Confidence Intervals

p. 246

Known [sigma] or a Large Sample

p. 246

A Computer Simulation

p. 251

Exercises

p. 253

Unknown Population Standard Deviation and a Small Sample

p. 254

Exercises

p. 260

A Confidence Interval for a Proportion

p. 260

Exercises

p. 263

Finite-Population Correction Factor

p. 263

Exercises

p. 264

Choosing an Appropriate Sample Size

p. 265

Exercises

p. 267

Chapter Outline

p. 268

Pronunciation Key

p. 269

Chapter Exercises

p. 269

exercises.com

p. 272

Dataset Exercises

p. 273

Software Commands

p. 273

Answers to Self-Review

p. 275

One-Sample Tests of Hypothesis

p. 276

Introduction

p. 277

What Is a Hypothesis?

p. 277

What Is Hypothesis Testing?

p. 278

Five-Step Procedure for Testing a Hypothesis

p. 278

State the Null Hypothesis (H[subscript 0]) and the Alternate Hypothesis (H[subscript 1])

p. 278

Select a Level of Significance

p. 279

Select the Test Statistic

p. 279

Formulate the Decision Rule

p. 281

Make a Decision

p. 282

One-Tailed and Two-Tailed Tests of Significance

p. 283

Testing for a Population Mean with a Known Population Standard Deviation

p. 284

A Two-Tailed Test

p. 284

A One-Tailed Test

p. 288

p-Value in Hypothesis Testing

p. 288

Testing for a Population Mean: Large Sample, Population Standard Deviation Unknown

p. 290

Exercises

p. 291

Tests Concerning Proportions

p. 292

Exercises

p. 295

Testing for a Population Mean: Small Sample, Population Standard Deviation Unknown

p. 295

Exercises

p. 300

A Software Solution

p. 301

Exercises

p. 303

Chapter Outline

p. 304

Pronunciation Key

p. 305

Chapter Exercises

p. 305

exercises.com

p. 309

Dataset Exercises

p. 309

Software Commands

p. 310

Answers to Self-Review

p. 311

Two-Sample Tests of Hypothesis

p. 312

Introduction

p. 313

Two-Sample Tests of Hypothesis: Independent Samples

p. 313

Exercises

p. 318

Two-Sample Tests about Proportions

p. 319

Exercises

p. 321

Comparing Population Means with Small Samples

p. 323

Exercises

p. 326

Two-Sample Tests of Hypothesis: Dependent Samples

p. 327

Comparing Dependent and Independent Samples

p. 331

Exercises

p. 333

Chapter Outline

p. 334

Pronunciation Key

p. 335

Chapter Exercises

p. 335

exercises.com

p. 340

Dataset Exercises

p. 341

Software Commands

p. 341

Answers to Self-Review

p. 342

Analysis of Variance

p. 344

Introduction

p. 345

The F Distribution

p. 345

Comparing Two Population Variances

p. 346

Exercises

p. 349

ANOVA Assumptions

p. 350

The ANOVA Test

p. 352

Exercises

p. 359

Inferences about Pairs of Treatment Means

p. 360

Exercises

p. 362

Chapter Outline

p. 364

Pronunciation Key

p. 365

Chapter Exercises

p. 365

exercises.com

p. 370

Dataset Exercises

p. 370

Software Commands

p. 371

Answers to Self-Review

p. 373

Linear Regression and Correlation

p. 374

Introduction

p. 375

What Is Correlation Analysis?

p. 375

The Coefficient of Correlation

p. 377

The Coefficient of Determination

p. 381

Correlation and Cause

p. 382

Exercises

p. 382

Testing the Significance of the Correlation Coefficient

p. 384

Exercises

p. 386

Regression Analysis

p. 386

Least Squares Principle

p. 386

Drawing the Line of Regression

p. 389

Exercises

p. 390

The Standard Error of Estimate

p. 392

Assumptions Underlying Linear Regression

p. 395

Exercises

p. 396

Confidence and Prediction Intervals

p. 396

Exercises

p. 400

More on the Coefficient of Determination

p. 400

Exercises

p. 403

The Relationships among the Coefficient of Correlation, the Coefficient of Determination, and the Standard Error of Estimate